Tone mapping

About: Tone mapping is a research topic. Over the lifetime, 1713 publications have been published within this topic receiving 48490 citations.

Beyond Tone Mapping: Enhanced Depiction of Tone Mapped HDR Images

Abstract: High Dynamic Range (HDR) images capture the full range of luminance present in real world scenes, and unlike Low Dynamic Range (LDR) images, can simultaneously contain detailed information in the deepest of shadows and the brightest of light sources. For display or aesthetic purposes, it is often necessary to perform tone mapping, which creates LDR depictions of HDR images at the cost of contrast information loss. The purpose of this work is two-fold: to analyze a displayed LDR image against its original HDR counterpart in terms of perceived contrast distortion, and to enhance the LDR depiction with perceptually driven colour adjustments to restore the original HDR contrast information. For analysis, we present a novel algorithm for the characterization of tone mapping distortion in terms of observed loss of global contrast, and loss of contour and texture details. We classify existing tone mapping operators accordingly. We measure both distortions with perceptual metrics that enable the automatic and meaningful enhancement of LDR depictions. For image enhancement, we identify artistic and photographic colour techniques from which we derive adjustments that create contrast with colour. The enhanced LDR image is an improved depiction of the original HDR image with restored contrast information.

Fast tone mapping for high dynamic range images

Abstract: We present a fast, effective and flexible tone reproduction method that preserves visibility and contrast impression of high dynamic range scenes in low dynamic range reproduction devices. A single parameter controls the visibility and contrast in a simple and elegant manner and at interactive speed. The new method is simple to use and is computationally highly efficient. Experiments show that the technique produces good results on a variety of high dynamic range images. The method can also be used to enhance ordinary low dynamic range digital images.

Biologically Inspired Blind Quality Assessment of Tone-Mapped Images

Abstract: Currently, many tone mapping operators (TMOs) have been provided to compress high dynamic range images to low dynamic range (LDR) images for visualizing them on the common displays. Since quality degradation is inevitably induced by compression, how to evaluate the obtained LDR images is indeed a headache problem. Until now, only a few full reference (FR) image quality assessment metrics have been proposed. However, they highly depend on reference image and neglect human visual system characteristics, hindering the practical applications. In this paper, we propose an effective blind quality assessment method of tone-mapped image without access to reference image. Inspired by that the performance of existing TMOs largely depend on the brightness and chromatic and structural properties of a scene, we evaluate the perceptual quality from the perspective of color information processing in the brain. Specifically, motivated by the physiological and psychological evidence, we simulate the responses of single-opponent (SO) and double-opponent (DO) cells, which play an important role in the processing of the color information. To represent the textural information, we extract three features from gray-level co-occurrence matrix (GLCM) calculated from SO responses. Meanwhile, both GLCM and local binary pattern descriptor are employed to extract texture and structure in the responses of DO cells. All these extracted features and associated subjective ratings are learned to reveal the connection between feature space and human opinion score. Extensive experiments demonstrate that the proposed method outperforms the state-of-the-art blind quality assessment methods and is comparable with the popular FR methods on two recently published tone-mapped image databases.

Natural hdr image tone mapping based on retinex

Abstract: In this paper, new k factor decision method and highlight compression operator are proposed to enhance the appearance and naturalness of rendered High Dynamic Range (HDR) images. The retinex algorithm is one of the outstanding local operators, which well preserves local contrast in highlights. However, the retinex algorithm gives a worse overall appearance and undistinguishable dark area contrast than global operators or other local operators in some cases. The most prominent improvement of the proposed method is that the decision method of the k factor, which is one of the parameters in retinex algorithm, is proposed by using the dynamic range in images. The proposed parameter decision method enhances the overall quality and preference of the image and solves any parameter setting problems. Also, dark area details become more distinguishable by the highlight compression operator. According to the results of many HDR image experiments, the proposed method shows better rendering in terms of naturalness and dark area details than the previous tone-mapping algorithm.1.

System and method for processing image data using an image signal processor having back-end processing logic

Abstract: Disclosed embodiments provide for a an image signal processing system 32 that includes back-end pixel processing unit 120 that receives pixel data after being processed by at least one of a front-end pixel processing unit 80 and a pixel processing pipeline 82. In certain embodiments, the back-end processing unit 120 receives luma/chroma image data and may be configured to apply face detection operations, local tone mapping, bright, contrast, color adjustments, as well as scaling. Further, the back-end processing unit 120 may also include a back-end statistics unit 2208 that may collect frequency statistics. The frequency statistics may be provided to an encoder 118 and may be used to determine quantization parameters that are to be applied to an image frame.